paradizelost/paperless-ngx
1
0
Fork 0
mirror of https://github.com/paperless-ngx/paperless-ngx.git synced 2025-04-25 10:49:30 -05:00
Code Issues Packages Projects Releases Wiki Activity

updated documentation

Browse Source
This commit is contained in:
Jonas Winkler 2020-11-18 22:56:30 +01:00
parent 0bc6d471fa
commit b89e836e3d
3 changed files with 25 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
docs/advanced_usage.rst
View File

@ -128,6 +128,8 @@ consumer. Once complete, you should see the newly-created document,
automatically tagged with the appropriate data.
.. _advanced-automatic_matching:
Automatic matching
==================

2
docs/changelog.rst
View File

@ -96,6 +96,8 @@ paperless-ng 0.9.0
sqlite.
* ``PAPERLESS_OCR_THREADS`` is gone and replaced with ``PAPERLESS_TASK_WORKERS`` and
``PAPERLESS_THREADS_PER_WORKER``. Refer to the config example for details.
* ``PAPERLESS_OPTIMIZE_THUMBNAILS`` allows you to disable or enable thumbnail
optimization. This is useful on less powerful devices.
* Many more small changes here and there. The usual stuff.

22
docs/faq.rst
View File

@ -23,12 +23,32 @@ is
**Q:** *Will paperless-ng run on Raspberry Pi?*
**A:** The short answer is yes. The long answer is that certain parts of
**A:** The short answer is yes. I've tested it on a Raspberry Pi 3 B.
The long answer is that certain parts of
Paperless will run very slow, such as the tesseract OCR. On Rasperry Pi,
try to OCR documents before feeding them into paperless so that paperless can
reuse the text. The web interface should be alot snappier, since it runs
in your browser and paperless has to do much less work to serve the data.
.. note::
Consider setting ``PAPERLESS_OPTIMIZE_THUMBNAILS`` to false to speed up
the consumption process. This takes quite a bit of time on Raspberry Pi.
.. note::
Updating the :ref:`automatic matching algorithm <advanced-automatic_matching>`
takes quite a bit of time. However, the update mechanism checks if your
data has changed before doing the heavy lifting. If you experience the
algorithm taking too much cpu time, consider changing the schedule in the
admin interface to daily or weekly. You can also manually invoke the task
by changing the date and time of the next run to today/now.
The actual matching of the algorithm is fast and works on Raspberry Pi as
well as on any other device.
**Q:** *How do I install paperless-ng on Raspberry Pi?*
**A:** There is not docker image for ARM available. If you know how to build